滿額折
商品簡介
商品簡介
Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.
This book begins explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and related terminologies in simple terms. You then will move on to ML applications in healthcare using case studies with coding. This is followed by looking at datasets in healthcare--EHR data with multi-task deep learning (DL). Next, you will go over a neurolinguistic programming (NLP) case study covering transfer learning in NLP. You also will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. There is a chapter on medical imaging analysis showing you how to deal with 2D and 3D images. The concluding section shows you how to build a Q&A system using a pre-trained transformer model. It also discusses Bio-Bert architecture to train your own Q&A system. And, lastly, you go through an ML application made live with Docker using Flask.
By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and DL tools and techniques to the healthcare industry. What You Will Learn
Data scientists and software developers interested in machine learning and its application in the healthcare industry
This book begins explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and related terminologies in simple terms. You then will move on to ML applications in healthcare using case studies with coding. This is followed by looking at datasets in healthcare--EHR data with multi-task deep learning (DL). Next, you will go over a neurolinguistic programming (NLP) case study covering transfer learning in NLP. You also will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. There is a chapter on medical imaging analysis showing you how to deal with 2D and 3D images. The concluding section shows you how to build a Q&A system using a pre-trained transformer model. It also discusses Bio-Bert architecture to train your own Q&A system. And, lastly, you go through an ML application made live with Docker using Flask.
By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and DL tools and techniques to the healthcare industry. What You Will Learn
- Understand the healthcare industry
- Design, develop, train, validate, and deploy machine learning models on healthcare data
- Be familiar with best practices for debugging and validating machine learning models
- Know how transfer learning and federated learning differ
Data scientists and software developers interested in machine learning and its application in the healthcare industry
購物須知
外文書商品之書封，為出版社提供之樣本。實際出貨商品，以出版社所提供之現有版本為主。部份書籍，因出版社供應狀況特殊，匯率將依實際狀況做調整。
無庫存之商品，在您完成訂單程序之後，將以空運的方式為你下單調貨。為了縮短等待的時間，建議您將外文書與其他商品分開下單，以獲得最快的取貨速度，平均調貨時間為1~2個月。
為了保護您的權益，「三民網路書店」提供會員七日商品鑑賞期(收到商品為起始日)。
若要辦理退貨，請在商品鑑賞期內寄回，且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。